LlamaIndex DevelopmentCustom Model Training & Distillation

Custom Models for LlamaIndex Retrieval

Train custom embedding and reranking models optimised for LlamaIndex retrieval pipelines. We fine-tune models that improve index quality and query accuracy for your domain.

LlamaIndex Development Capabilities for Custom Model Training & Distillation

LlamaIndex-optimised embedding training

Custom reranker fine-tuning

Index quality evaluation

Domain-specific retrieval tuning

Query performance benchmarking

Use Cases

1

Domain-tuned embeddings for LlamaIndex indices

2

Custom rerankers for LlamaIndex query engines

3

Specialised retrieval models for enterprise search

4

Fine-tuned synthesis models for LlamaIndex

Integration Details

LlamaIndex Development

LlamaIndex development for sophisticated retrieval systems. We build production RAG pipelines with advanced indexing, routing, and synthesis.

All major LLMsVector databasesDocument storesEnterprise dataEvaluation tools

Custom Model Training & Distillation

Training domain models on curated corpora, applying NeMo and LoRA distillation, and wiring evaluation harnesses so accuracy stays high while latency and spend drop.

NVIDIA NeMo MicroservicesHugging Face TransformersLoRA & QLoRADeepSpeed & MegatronRAG Evaluation HarnessesPromptFlow & TruLensWeights & Biases

Ready to Implement LlamaIndex Development for Custom Model Training & Distillation?

Let's discuss how we can help you leverage llamaindex development within your custom model training & distillation strategy.

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